Contains an updated string of the operations used to create the fuzzy set. For example, if you create a warm fuzzy set and then apply the VERY hedge, the Expression property would contain 'very warm' (Inherited from FuzzyLogic.TFuzzySet.)

Returns the XY value pairs that define the shape of the fuzzy set. Changing the X value can change the order of the XY value pairs, e.g., if you have three points ((0.3 0.3) (0.5 1) (1 0)), changing XValues[ 1] from 0.5 to 0 will cause the list to look like this: ((0 1) (0.3 0. 3) (1 0)).

Overloaded. Creates a beta curve to define the fuzzy set shape (bell shaped). The Num parameter indicates the number of points to use to define the curve. Center and range define the bell curve. InflectionPoint defines the point for the change in slope for the bell curve (Inherited from FuzzyLogic.TFuzzySet.)

Overloaded. Creates a beta curve to define the fuzzy set shape (bell shaped). The Num parameter indicates the number of points to use to define the curve. Center and range define the bell curve. InflectionPoint defines the point for the change in slope for the bell curve. Finally, Weight controls the strength of the bell shape. (Inherited from FuzzyLogic.TFuzzySet.)

Creates a growth or decline slope to define the fuzzy set shape. The Num parameter indicates the number of points to use to define the shape. Left defines when the slope starts to increase or decrease, and Right defines when the slope ends. InflectionPoint defines the point for the change in slope. Finally, the Growth parameter controls whether a growth or decline slope is created. (Inherited from FuzzyLogic.TFuzzySet.)

Overloaded. Creates a PI curve to define the fuzzy set shape (bell shape). The Num parameter indicates the number of points to use to define the curve. Center defines the center (top point) of the bell curve. Range defines the ends of the bell curve. (Inherited from FuzzyLogic.TFuzzySet.)

Overloaded. Creates a PI curve to define the fuzzy set shape (bell shape). The Num parameter indicates the number of points to use to define the curve. Center defines the center (top point) of the bell curve. Left and Right define the ends of the bell curve. (Inherited from FuzzyLogic.TFuzzySet.)

Overloaded. Returns the strength of the match between the fuzzy set and the Match fuzzy set. It is calculated based on the maximum value in the intersection of the two fuzzy sets (Inherited from FuzzyLogic.TFuzzySet.)

Overloaded. Modifies the fuzzy set using the specified hedge type. The current fuzzy set is returned, not a new fuzzy set. This method applies the basic hedge modifications, such as minus, plus, product, etc

Overloaded. Returns a fuzzy set which represents the consequent of a correlation rule (see AssertRule), where the current fuzzy set is modified by the NewEvidence fuzzy set. (Inherited from FuzzyLogic.TFuzzySet.)

Overloaded. Returns a fuzzy set which represents the consequent of a correlation rule (see AssertRule), where the current fuzzy set is modified by the NewEvidence fuzzy set. (Inherited from FuzzyLogic.TFuzzySet.)

Overloaded. Returns a new fuzzy set representing the intersection (AND) of the current fuzzy set with the FuzzySet parameter, e.g, hot AND cold. It uses the specified operation for calculating the intersection.

Overloaded. Returns a new fuzzy set representing the intersection (AND) of the current fuzzy set with the FuzzySet parameter, e.g, hot AND cold. It uses the specified operation for calculating the intersection. (Inherited from FuzzyLogic.TFuzzySet.)

Returns TRUE if the current fuzzy set intersects the passed in fuzzy set. Two fuzzy sets intersect if at any point in the universe of discourse (between XMinimum and XMaximum), both fuzzy sets have non- zero memberships

Overloaded. Iterates through all the points in Self and the FuzzySet parameter, and calls the fuzzy operator at each point. No FuzzySet is returned. If the Fuzzy Operator function returns True it means that this method should abort and this method returns True.

Normalizes the current fuzzy set and returns itself. Normalization acts to "stretch" the fuzzy set vertically. It finds the maximum Y value in the fuzzy set, scales that value up to 1 and then scales the rest of the fuzzy set by that amount.

Overloaded. Iterates through all the points in Self and FuzzySet and calls operator on the points. However, unlike Iterate, it creates a new fuzzy set created by the FuzzyOperator (it is the responsibility of the FuzzyOperator to add points to the result fuzzy set). If the Fuzzy Operator function returns True it means that this method should abort.

Overloaded. Returns a new fuzzy set representing the union (OR) of the current fuzzy set with the FuzzySet parameter, e.g, hot OR cold. It uses the specified operation for calculating the intersection.

Overloaded. Returns a new fuzzy set representing the union (OR) of the current fuzzy set with the FuzzySet parameter, e.g, hot OR cold. It uses the specified operation for calculating the intersection. (Inherited from FuzzyLogic.TFuzzySet.)

Each fuzzy set defines the meaning of one term (or value) in the fuzzy variable. For example, the fuzzy variable "temperature" could have sets for the terms: cold, warm, and hot. Fuzzy sets describe a fuzzy value, meaning that it has imprecise or fuzzy boundaries describing the value. Classical logic defines terms with crisp boundaries: Cold is TRUE when the value is between 0 and 32, FALSE otherwise. The fuzzy set cold could have values stating that it is definitely cold (100%) when the temperature is less than 20, As the temperature increases between 21 and 32 degrees, the chance of being considered cold drops down to 50%, 50-40% chance from 33 - 50 degrees, etc.

Fuzzy Set truth values are determined by the XY value pairs that make up their "shape". The XY value pairs define a 2D plot. The X range varies over the universe of discourse. The Y Range varies from 0 ( completely not a member) to 1 (completely a member). For example, the fuzzy set cold above would have the following XY value pairs: ((20 1) (32 0.5) (50 0.4) (60 0)).